Sparse-grid sampling recovery and numerical integration of functions having mixed smoothness

Fuente: arXiv
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Main Author: Dũng, Dinh
Format: Preprint
Published: 2023
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author Dũng, Dinh
author_facet Dũng, Dinh
contents We give a short survey of recent results on sparse-grid linear algorithms of approximate recovery and integration of functions possessing a unweighted or weighted Sobolev mixed smoothness based on their sampled values at a certain finite set. Some of them are extended to more general cases.
format Preprint
id arxiv_https___arxiv_org_abs_2309_04994
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Sparse-grid sampling recovery and numerical integration of functions having mixed smoothness
Dũng, Dinh
Numerical Analysis
We give a short survey of recent results on sparse-grid linear algorithms of approximate recovery and integration of functions possessing a unweighted or weighted Sobolev mixed smoothness based on their sampled values at a certain finite set. Some of them are extended to more general cases.
title Sparse-grid sampling recovery and numerical integration of functions having mixed smoothness
topic Numerical Analysis
url https://arxiv.org/abs/2309.04994